Improving the visualization of rainfall trends using various innovative trend methodologies with time–frequency-based methods

Abstract

In this paper, the Innovative Trend Methodology (ITM) and their inspired approaches, i.e., Double (D-ITM) and Triple (T-ITM), were combined with Hilbert Huang transform (HHT) time frequency-based method. The new hybrid methods (i.e., ITM-HHT, D-ITM-HHT, and T-ITM-HHT) were proposed and compared to the DWT-based methods in order to recommend the best method. Three total annual rainfall time series from 1920 to 2011 were selected from three hydrological basins in Northern Algeria. The new combined models (ITM-HHT, D-ITM-HHT, and T-ITM-HHT) revealed that the 1950–1975 period has significant wet episodes followed by a long-term drought observed in the western region of Northern Algeria, while Northeastern Algeria presented a wet period since 2001. The proposed approaches successfully detected, in a visible manner, hidden trends presented in the signals, which proves that the removal of some modes of variability from the original rainfall signals can increase the accuracy of the used approaches.

Artificial intelligent systems optimized by metaheuristic algorithms and teleconnection indices for rainfall modeling: The case of a humid region in the mediterranean basin

“…The significance of applied climatology increased after World War II, with numerous studies being published addressing the direct impacts of climate [ 2 , 3 ]. Knowledge of rainfall data and characteristics is indispensable for water planning and management [ [4] , [5] , [6] , [7] ]. Several studies have assessed the spatiotemporal rainfall change and variability worldwide [ [8] , [9] , [10] , [11] , [12] , [13] , [14] ].…”

Assessment of hybrid machine learning algorithms using TRMM rainfall data for daily inflow forecasting in Três Marias Reservoir, eastern Brazil

“…Efficient water resource management has always played a crucial role in driving economic progress [ 1 , 2 ]. With growing water demand and challenges posed by prolonged droughts and climate uncertainties largely attributed to climate change, effective management of surface water reservoirs has become more important than ever.…”

Evaluation of annual total precipitation in the transboundary Euphrates–Tigris River Basin of Türkiye using innovative graphical and statistical trend approaches

“…Many studies on climate change are carried out by researchers all over the world, and the spatial and temporal variability of the hydrological cycle components is examined (Bouklikha et al 2021;Saplıoğlu and Güçlü 2022;Koycegiz and Buyukyildiz 2019;Zerouali et al 2022;Özel et al 2004;Zhu et al 2020). For this purpose, various trend methods are used, both parametric and nonparametric, as well as providing statistical and graphical evaluation.…”